The present invention relates to photolithography, and more particularly to the testing a photomask.
Processing to convert design data representing a layout into a photomask is an arduous and time-consuming process, as is the verification of a photomask after manufacture. In a typical process of designing an integrated circuit, a circuit designer creates a set of design data for a new circuit. The design data typically represents a set of elements interconnected to form circuits, which are interconnected to form functional units, which themselves make up an integrated circuit. Alternatively, the design data may represent a set of previously designed circuit blocks which are interconnected to form the functional units of the integrated circuit. Using several stages of processing, design data is converted to a set of “mask data” representing a photomask for printing the layout. The set of mask data can then be verified for conformity to a set of design rules and then processed for optical proximity correction (“OPC”). Alternatively, the initial mask data is immediately processed for OPC. The goal of OPC is to ensure that each feature of the layout can be printed acceptably with the mask, by correcting for the presence of nearby features of the mask that cause destructive and/or constructive interference as during the mask fabrication, and wafer lithography process. Through OPC, some features of the mask are increased in size, other features are decreased in size, and the placement and shape of certain features of the mask are changed. Like optical design rules checking, OPC is performed on a set of mask data prior to using the mask data to construct an actual physical mask. However, even after OPC, the features which appear in the mask data must be verified to be present on the mask, so that they can be printed acceptably on a substrate as features of a layout. Conventionally, some of this verification is performed as checking of the mask data against mask design rules. Sometimes, a computer has been used to perform simulations to determine the results of patterning the features of a layout represented by the mask data prior to using the mask data to prepare the physical mask, which is known as optical rules checking (“ORC”).
In some prior art systems as noted above, ORC is used on a set of mask data prior to OPC processing to verify that the mask represented by the mask data will succeed in printing the features of a layout. However, there are several fundamental problems with this approach. First, ORC is only capable of detecting design problems. Second, the same mask data is used for simulation according to ORC that was generated during OPC, such that errors which are generated by OPC are not detected by ORC. A third problem is that the simulations required to perform sufficient ORC to verify the mask data for one mask consume much time and computing resources, and for that reason, are expensive to perform. Fourth, the trustworthiness of ORC in verifying mask data is continually subject to heightened scrutiny, because ORC is performed on mask data that does not represent actual feature patterns on a mask, as the mask production process introduces some non-ideality. In addition, systems capable of recognizing images and/or detecting defects using ORC are as yet in their infancy, and have difficulty discerning true problems from false calls.
Alternatively, after the mask is manufactured, its features can be verified by imaging the mask, either under actinic or non-actinic exposure conditions to obtain mask inspection data. The results of patterning features are then obtained by simulating lithographic processing in accordance with the mask as represented by the mask inspection data. However, in the past such simulations have been generally performed under a variety of lithographic process conditions including both “best” and “worst” lithographic exposure conditions and many conditions in between the best and worst conditions. A variety of conditions have to be simulated include different conditions for focus, dose, assumptions concerning the ideality of lenses, as well as assumptions concerning conditions achieved for substrates, photoresist films, lithography tools and other pertinent components of obtaining an exposure.
However, simulations under such conditions can consume much time and resources. Thus, computer simulations are typically performed with only a few of the conditions and components of the lithographic exposure being varied. However, if it is desired to perform more complete testing according to this algorithm to simulate all of the variable conditions and combinations of conditions of the lithographic exposure for a desired process window, dozens of simulations would be required for each location of the physical layout to be produced by the mask. In view of the millions of locations of a layout to be printed with a mask, it is evident that the task of simulating all combinations of the variable conditions of the lithographic exposure for the whole layout becomes impossible to perform using the limited computing resources and time that are normally allocated thereto. However, if any possible conditions are omitted, such testing can be inadequate to detect problems in the mask where the process window is unusually narrow. If such problem goes undetected prior to constructing the actual physical mask, then when the mask is constructed, the mask may be unusable, leading to potentially severe delays in manufacturing, and potentially causing unrecoverable loss of product revenue.
Moreover, the same concerns apply to computer-based simulations using actinic and/or non-actinic mask inspection data for determining mask defects and for verifying the printability of certain “designed images” of a layout. Again, it can be cost-prohibitive to perform computer-based simulation of all the combinations of variable lithographic exposure conditions to determine mask defects for all of the locations of a layout and to verify printability of designed images.
Accordingly, it would be desirable to provide an improved method of testing a photomask which can be used to more readily verify the performance of the photomask, which has the potential to require much less computing resources and/or time to perform than the conventional approaches discussed above.